Abstract

Abstract. One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the preprocessing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) (Hill et al., 2004) and TempestRemap (Ullrich et al., 2013) offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) (Larson et al., 2001) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multistep processes present several hurdles in terms of the scientific workflow and impede research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) (Tautges et al., 2004; Mahadevan et al., 2015) library, which allows for a complete description of the numerical grids and solution data used in each submodel. Through a scalable advancing-front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative, and monotonicity-preserving remapping weights between discretization specifications. The Fortran-compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process. We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-the-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral element atmosphere and finite volume discretizations on the polygonal ocean grids.

Highlights

  • Understanding Earth’s climate evolution through robust and accurate modeling of the intrinsically complex, coupled ocean–atmosphere–land–ice–biosphere models requires extreme-scale computational power (Washington et al, 2008)

  • One factor contributing to the spatiotemporal accuracy is the mapping between different discretizations of the sphere used in the components of a coupled climate model

  • We present a new infrastructure with scalable algorithms implemented using the Mesh Oriented datABase (MOAB) mesh library and TempestRemap package to replace the Earth System Modeling Framework (ESMF)-E3SM-Model Coupling Toolkit (MCT) remapper/coupler workflow

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Summary

Introduction

Understanding Earth’s climate evolution through robust and accurate modeling of the intrinsically complex, coupled ocean–atmosphere–land–ice–biosphere models requires extreme-scale computational power (Washington et al, 2008). This process flow prohibits the component solvers from performing any runtime spatial adaptivity, since the remapping weights have to be recomputed dynamically after any changes in grid positions

Background
Algorithmic approach
Interfacing to component models in E3SM
Migration of component mesh to coupler
Computing the regridding operator
Advancing-front intersection – a linear complexity algorithm
Parallel implementation considerations
Computation of a source coverage mesh
This interpolator
Note on MBTR remapper implementation
Results
Serial performance
TempestRemap
Scalability of the MOAB Kd-tree point locator
The parallel MBTR remapping algorithm
Effect of partitioning strategy
Note on application of weights
Full Text
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